Showing 1,121 - 1,140 results of 1,301 for search '(("wrapping" OR "mapping") OR "trapping")', query time: 0.09s Refine Results
  1. 1121
  2. 1122

    Bird-Count: a multi-modality benchmark and system for bird population counting in the wild by Wang, Hongchang, Lu, Huaxiang, Guo, Huimin, Jian, Haifang, Gan, Chuang, Liu, Wu

    Published 2023
    “…To mitigate these challenges, a simple yet effective plug-and-play framework, called Morphology Prior Knowledge Fusion Network (MPKNet), which can be used on-site to help generate a high-precision bird population density map by incorporating morphological prior knowledge, is proposed. …”
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    Article
  3. 1123

    Label-free discrimination of tumorigenesis stages using in vitro prostate cancer bone metastasis model by Raman imaging by Kar, Sumanta, Jaswandkar, Sharad V., Katti, Kalpana S., Kang, Jeon Woong, So, Peter T. C., Paulmurugan, Ramasamy, Liepmann, Dorian, Venkatesan, Renugopalakrishnan, Katti, Dinesh R.

    Published 2024
    “…Our results showed distinctive spectral differences in Raman imaging between prostate cancer cells and the cells cultured in 3D bone mimetic scaffolds, particularly at 1002, 1261, 1444, and 1654 cm<jats:sup>−1</jats:sup>, which primarily contain proteins and lipids signals. Raman maps capture sub-cellular responses with the progression of tumor cells into metastasis. …”
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    Article
  4. 1124

    Uncovering Fast Solid-Acid Proton Conductors Based on Dynamics of Polyanion Groups and Proton Bonding Strength by Žguns, Pjotrs, Klyukin, Konstantin, Wang, Louis S., Xiong, Grace, Li, Ju, Haile, Sossina M., Yildiz, Bilge

    Published 2024
    “…In this work, we have mapped the structural, chemical and dynamic properties of solid acids to the elementary steps of the Grotthuss mechanism of proton diffusion. …”
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    Article
  5. 1125
  6. 1126

    Information FOMO: The Unhealthy Fear of Missing Out on Information&mdash;A Method for Removing Misleading Data for Healthier Models by Pickering, Ethan, Sapsis, Themistoklis P.

    Published 2024
    “…We find these instabilities are a result of the complexity of the underlying map and are linked to extreme events and heavy tails. …”
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    Article
  7. 1127
  8. 1128

    Neural Light Transport for Relighting and View Synthesis by Zhang, Xiuming, Fanello, Sean, Tsai, Yun-Ta, Sun, Tiancheng, Xue, Tianfan, Pandey?, Rohit, Orts-Escolano, Sergio, Davidson?, Philip, Rhemann, Christoph, Debevec?, Paul, Barron, Jonathan T., Ramamoorthi, Ravi, Freeman, William

    Published 2025
    “…With this learned LT, one can relight the scene photorealistically with a directional light or an HDRI map, synthesize novel views with view-dependent effects, or do both simultaneously, all in a unified framework using a set of sparse observations.…”
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    Article
  9. 1129

    RoboGrammar: Graph Grammar for Terrain-Optimized Robot Design by Zhao, Allan, Xu, Jie, Konakovic-Lukovic, Mina, Hughes, Josephine, Spielberg, Andrew, Rus, Daniela, Matusik, Wojciech

    Published 2025
    “…In Graph Heuristic Search, we explore the design space while simultaneously learning a function that maps incomplete designs (e.g., nodes in the combinatorial search tree) to the best performance values that can be achieved by expanding these incomplete designs. …”
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    Article
  10. 1130

    Television food advertising towards children : a content analysis of the Singapore advertising landscape and experimental study on the placement of pro-nutritional advertisements by Lim, Glenn Yin De., Lin, Jieying., Tang, Shuxia., Chen, Wendy Jin Jing.

    Published 2011
    “…This study aims to examine food and beverage (F&B) advertising as well as persuasion strategies in health communication in the form of pro-nutritional advertisements, in the context of children’s television viewing. In Study One, we mapped out the food advertising landscape by content analyzing F&B advertisements (ads) across six television channels over two weeks in Singapore. …”
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    Final Year Project (FYP)
  11. 1131

    Risk assessment model for UAV cost-effective path planning in urban environments by Hu, Xinting, Pang, Bizhao, Dai, Fuqing, Low, Kin Huat

    Published 2021
    “…We then computed the total risk and generated a risk cost map for path planning. Modified path planning algorithms were used to produce a cost-effective path, and we compared their performances in terms of total risk cost and computational time. …”
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    Journal Article
  12. 1132

    Rare bioparticle detection via deep metric learning by Luo, Shaobo, Shi, Yuzhi, Chin, Lip Ket, Zhang, Yi, Wen, Bihan, Sun, Ying, Nguyen, Binh T. T., Chierchia, Giovanni, Talbot, Hugues, Bourouina, Tarik, Jiang, Xudong, Liu, Ai-Qun

    Published 2021
    “…Deep metric learning offers a better generatability by using distance information to model the similarity of the images and learning function maps from image pixels to a latent space, playing a vital role in rare object detection. …”
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    Journal Article
  13. 1133

    Vehicle re-identification using machine learning by Tang, Lisha

    Published 2022
    “…Experimental results show that our approach outperforms recent state-of-the-art methods by averagely 2.63% in CMC@1 on VehicleID and 2.2% in mAP on VeRi776.…”
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    Thesis-Master by Research
  14. 1134

    Deep Koopman operator-informed safety command governor for autonomous vehicles by Chen, Hao, He, Xiangkun, Cheng, Shuo, Lv, Chen

    Published 2024
    “…However, Koopman operator maps the original nonlinear system into an infinite-dimensional linear space to achieve global linearization of the nonlinear system through input and output data, which derives an absolute equivalent linear representation of the original state space. …”
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    Journal Article
  15. 1135

    Development of the polyglot Asian medicine knowledge graph system by Khoo, Christopher S. G., Stanley-Baker, Michael, Faizah Binte Zakaria, Chen, Jinju, Ang, Shaun Qiao Rou, Huang, Bo

    Published 2024
    “…The paper describes how the knowledge graph was derived based on a dataset comprising over 25 Microsoft Excel spreadsheets, and how the spreadsheet data were processed and mapped to the graph database using upload scripts in the Neo4j Cypher graph query language. …”
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    Conference Paper
  16. 1136

    Super enhancer acquisition drives expression of oncogenic PPP1R15B that regulates protein homeostasis in multiple myeloma by Xiong, Sinan, Zhou, Jianbiao, Tan, Tze King, Chung, Tae-Hoon, Tan, Tuan Zea, Toh, Sabrina Hui-Min, Tang, Nicole Xin Ning, Jia, Yunlu, See, Yi Xiang, Fullwood, Melissa Jane, Sanda, Takaomi, Chng, Wee-Joo

    Published 2024
    “…Here we generate a high-resolution contact map of myeloma-associated super-enhancers by integrating H3K27ac ChIP-seq and HiChIP from myeloma cell lines, patient-derived myeloma cells and normal plasma cells. …”
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    Journal Article
  17. 1137

    Smart sleep monitoring: sparse sensor-based spatiotemporal CNN for sleep posture detection by Hu, Dikun, Gao, Weidong, Ang, Kai Keng, Hu, Mengjiao, Chuai, Gang, Huang, Rong

    Published 2024
    “…This S3CNN holistically incorporates a pair of spatial convolution neural networks to capture cardiorespiratory activity maps and a pair of temporal convolution neural networks to capture the heart rate and respiratory rate. …”
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    Journal Article
  18. 1138

    Secure image encryption based on an ideal new nonlinear discrete dynamical system by Lin, M. Rongming, Ng, Teng Yong

    Published 2018
    “…It is well known that encryption algorithms developed based on Logistic map suffer from limited key space due to the narrow regions of system parameters which can be used, potential risk of security in the presence of numerous periodic windows within the key space, and weakness in known-plain-text attack due to the inherent correlation among the chaotic sequence used for encryption. …”
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    Journal Article
  19. 1139

    Canonical Diffeomorphisms of Manifolds Near Spheres by Wang, Bing, Zhao, Xinrui

    Published 2023
    “…Let $$\{f_i\}_{i=1}^{n+1}$$ { f i } i = 1 n + 1 be the first $$(n+1)$$ ( n + 1 ) -eigenfunctions of (M, g) and $$f=(f_1, f_2, \ldots , f_{n+1})$$ f = ( f 1 , f 2 , … , f n + 1 ) . Then the map $${\tilde{f}}=\frac{f}{|f|}: M \rightarrow S^n$$ f ~ = f | f | : M → S n provides a diffeomorphism, and $${\tilde{f}}$$ f ~ satisfies a uniform bi-Hölder estimate. …”
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    Article
  20. 1140

    Deep Learning Based Prediction of Pulmonary Hypertension in Newborns Using Echocardiograms by Ragnarsdottir, Hanna, Ozkan, Ece, Michel, Holger, Chin-Cheong, Kieran, Manduchi, Laura, Wellmann, Sven, Vogt, Julia E.

    Published 2024
    “…We complement our predictions with saliency maps and show that the learned model focuses on clinically relevant cardiac structures, motivating its usage in clinical practice. …”
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    Article